Posted:November 2, 2015

The Ten Premises of KBAI

Inherent in Structured Dynamics‘ discussions about knowledge-based artificial intelligence (KBAI) have been some embedded premises. Some of my prior articles — and future ones to come — elaborate more fully on one or more of these points:

The electronic availability of content-rich knowledge bases has been the most important catalyst for recent AI advances in natural language and information processing

Wikipedia, and its DBpedia and now Wikidata derivatives, has been the most important source of concept and entity information for these purposes

None of these sources is coherently organized; attempts to use lexical relationships (WordNet) or Wikipedia itself (DBpedia ontology) to re-organize the content are also not coherent

Despite this incoherence, these knowledge bases have already been used to train many distant supervised machine learning applications; but, in efforts to date, each application has been manually trained, which is inefficient and time consuming

Fortunately, these knowledge bases can be mapped to a coherent structure; there are perhaps options; we have chosen Cyc

Once the potential role of KBs to inform machine learning is understood, the usefulness becomes obvious to re-express the KBs to maximize the features available for machine learning, including disjointedness assertions to enable selection of positive and negative training sets

Specific aspects of the KBs for which such re-organization is appropriate include concepts, types, entities, relations, events, attributes and statements

Therefore, a systematic re-organization of these KBs to support feature and training set generation can help automate and lower the cost of machine learning pipelines

Once these features and aspects are established, the result becomes a grounding structure, which can facilitate mappings to other knowledge structures, data interoperability and information integration

These same principles can be applied to existing or new knowledge bases, thereby increasing the scope and usefulness of the knowledge structure in a virtuous circle.

Precise definitions for all of the italicized terms are provided in the related glossary.